AIMC Topic: Deep Learning

Clear Filters Showing 19481 to 19490 of 28423 articles

A Molecular Image-Based Novel Quantitative Structure-Activity Relationship Approach, Deepsnap-Deep Learning and Machine Learning.

Current issues in molecular biology
The quantitative structure-activity relationship (QSAR) approach has been used in numerous chemical compounds as computational assessment for a long time. Further, owing to the high-performance modeling of QSAR, machine learning methods have been de...

Image registration: Maximum likelihood, minimum entropy and deep learning.

Medical image analysis
In this work, we propose a theoretical framework based on maximum profile likelihood for pairwise and groupwise registration. By an asymptotic analysis, we demonstrate that maximum profile likelihood registration minimizes an upper bound on the joint...

Deep learning algorithms for brain disease detection with magnetic induction tomography.

Medical physics
PURPOSE: In order to improve the reconstruction accuracy of magnetic induction tomography (MIT) and achieve fast imaging especially in the detection of cerebral hemorrhage, artificial intelligence algorithms are proposed to improve the accuracy of MI...

Deep-Learning-Based Prediction of High-Risk Taxi Drivers Using Wellness Data.

International journal of environmental research and public health
BACKGROUND: Factors related to the wellness of taxi drivers are important for identifying high-risk drivers based on human factors. The purpose of this study is to predict high-risk taxi drivers based on a deep learning method by identifying the well...

Deep learning-based real-time volumetric imaging for lung stereotactic body radiation therapy: a proof of concept study.

Physics in medicine and biology
Due to the inter- and intra- variation of respiratory motion, it is highly desired to provide real-time volumetric images during the treatment delivery of lung stereotactic body radiation therapy (SBRT) for accurate and active motion management. In t...

A physics-guided modular deep-learning based automated framework for tumor segmentation in PET.

Physics in medicine and biology
An important need exists for reliable positron emission tomography (PET) tumor-segmentation methods for tasks such as PET-based radiation-therapy planning and reliable quantification of volumetric and radiomic features. To address this need, we propo...

Classification of Color-Coded Scheimpflug Camera Corneal Tomography Images Using Deep Learning.

Translational vision science & technology
PURPOSE: To assess the use of deep learning for high-performance image classification of color-coded corneal maps obtained using a Scheimpflug camera.

Denoising Autoencoder, A Deep Learning Algorithm, Aids the Identification of A Novel Molecular Signature of Lung Adenocarcinoma.

Genomics, proteomics & bioinformatics
Precise biomarker development is a key step in disease management. However, most of the published biomarkers were derived from a relatively small number of samples with supervised approaches. Recent advances in unsupervised machine learning promise t...

Development and Prospective Validation of a Deep Learning Algorithm for Predicting Need for Mechanical Ventilation.

Chest
BACKGROUND: Objective and early identification of hospitalized patients, and particularly those with novel coronavirus disease 2019 (COVID-19), who may require mechanical ventilation (MV) may aid in delivering timely treatment.

Automated age estimation of young individuals based on 3D knee MRI using deep learning.

International journal of legal medicine
Age estimation is a crucial element of forensic medicine to assess the chronological age of living individuals without or lacking valid legal documentation. Methods used in practice are labor-intensive, subjective, and frequently comprise radiation e...